We examine the global organization of growing networks in which a new vertex is attached to already existing ones with a probability depending on their age. We find that the network is infinite or finite dimensional depending on whether the attachment probability decays slower or faster than (age)-1. The network becomes one dimensional when the attachment probability decays faster than (age)-2. We describe structural characteristics of these phases and transitions between them
We consider a class of complex networks whose nodes assume one of several possible states at any tim...
In many social complex systems, in which agents are linked by non-linear interactions, the history o...
This thesis consists of studies of network processes with an emphasis on phase transitions. Various ...
Complex networks describe a wide range of systems and structures in the world. Any real network can ...
In this paper, the dynamical behaviors of a class of weighted local-world evolving networks with agi...
We investigate the growth of connectivity in a network. In our model, starting with a set of disjoin...
Many social, biological, and technological networks display substantial non-trivial topological feat...
We propose a new preferential attachment–based network growth model in order to explain two properti...
33 pages, 3 figuresWe introduce a new oriented evolving graph model inspired by biological networks....
We propose a new preferential attachment-based network growth model in order to explain two properti...
Network models with preferential attachment, where new nodes are injected into the network and form ...
A basic premise behind the study of large networks is that interaction leads to complex collective b...
Preferential attachment drives the evolution of many complex networks. Its analytical studies mostly...
In many social complex systems, in which agents are linked by non-linear interactions, the history o...
Complex networks (systems) as a phenomenon can be observed by a wide range of networks in nature and...
We consider a class of complex networks whose nodes assume one of several possible states at any tim...
In many social complex systems, in which agents are linked by non-linear interactions, the history o...
This thesis consists of studies of network processes with an emphasis on phase transitions. Various ...
Complex networks describe a wide range of systems and structures in the world. Any real network can ...
In this paper, the dynamical behaviors of a class of weighted local-world evolving networks with agi...
We investigate the growth of connectivity in a network. In our model, starting with a set of disjoin...
Many social, biological, and technological networks display substantial non-trivial topological feat...
We propose a new preferential attachment–based network growth model in order to explain two properti...
33 pages, 3 figuresWe introduce a new oriented evolving graph model inspired by biological networks....
We propose a new preferential attachment-based network growth model in order to explain two properti...
Network models with preferential attachment, where new nodes are injected into the network and form ...
A basic premise behind the study of large networks is that interaction leads to complex collective b...
Preferential attachment drives the evolution of many complex networks. Its analytical studies mostly...
In many social complex systems, in which agents are linked by non-linear interactions, the history o...
Complex networks (systems) as a phenomenon can be observed by a wide range of networks in nature and...
We consider a class of complex networks whose nodes assume one of several possible states at any tim...
In many social complex systems, in which agents are linked by non-linear interactions, the history o...
This thesis consists of studies of network processes with an emphasis on phase transitions. Various ...